Analytical processing systems consume tables of data which are typically linked together by relationships that simplify the storage of data and make queries of the data more efficient. A standardized query language, such as Structured Query Language (SQL), can be used for creating and operating relational databases. Analytics involving statistical and other numerical procedures is the application of computer technology to solve problems in business and industry. The science of analytics is concerned with extracting useful properties of data using computable functions and, generally speaking, involves the extraction of desired properties of data sets from large databases.
Massively parallel processing (MPP) cluster database architectures deploy many computing nodes usually in a local high bandwidth network. MPP database architectures not only partition and manage data across computing nodes, but may also redundantly store data in replication nodes for data security and high performance query processing. Online analytical processing (OLAP) functions in MPP databases may flood the network with data rows moving from storage nodes to function processing nodes according to OLAP data partition specification. Typically, OLAP function processing starts after each function processing node receives the complete data partition set.